As per a Gartner report, over 30% of GenAI projects will be dropped by 2026 due to poor data quality, high costs or unclear business value.

Your 4-step blueprint for GenAI success

1. Assess your current data capabilities and needs

Use a data & analytics maturity model to understand your organization’s maturity level – this stock taking is crucial to the success of your data strategy.

• Are you at an aspiration stage, where you will focus on building a strong data foundation and basic analytics capabilities?
• Or have you progressed to having the capability, where you can prioritize building a data science team and advanced analytics skills?
• Or have your team reached a point of competency, where you are ready to start exploring GenAI applications?

A good data and analytics strategy starts with a clear vision. Gartner

In addition to your organization’s maturity level, evaluate your team’s skills and knowledge in AI and machine learning. Identify any skill gaps that need to be addressed through training or hiring. Consider the availability of specialized AI talent within your organization or the potential to partner with external experts. By understanding your team’s capabilities, you can create a roadmap for skill development, allowing you to focus on immediate needs while planning for future expansion plans.

2. Build a robust modern data foundation

One of the first steps in harnessing GenAI is to break down data silos within your organization. Often, crucial data is scattered across multiple platforms, making it difficult to get a unified view. Collecting, integrating and processing this data into a single, cohesive platform is essential for effective AI application.

Think of a retailer with customer data locked in outdated systems. By consolidating this data, they can unlock powerful insights and deliver personalized customer experiences.

Once integrated, it’s vital to ensure the data is clean, well-governed and secure. Poor data quality can lead to flawed AI outputs, while weak governance and security can expose your organization to risks. Building a modern data foundation with these principles in mind will lay the groundwork for reliable and impactful AI applications.

3. Make the right technology and model choices for your GenAI & data needs

Choosing the right technology and AI models is crucial for project success. Consider factors like your team’s expertise, available data and cost. If your team is comfortable with open-source models like Hugging Face or GPT, they offer flexibility but require more maintenance. Managed models like Amazon Bedrock or SageMaker are easier to implement with less upkeep but offer less customization.

Balancing these factors is key to a successful AI implementation. Opt for solutions that your team can manage effectively, that leverage your available data, and that fit within your budget. A well-thought-out choice here can save you time and money in the long run while ensuring robust performance.

Remember, AI performance is not just about speed and processing power; it is about delivering these results without ballooning costs. Proprietary systems can inflate total cost of ownership (TCO) with specialized hardware, licensing fees, and other hidden costs that make scaling more expensive in the long term.

One of the common misconceptions is that all AI workloads must run on expensive GPUs, which, while powerful, are not always the most efficient or necessary option for every type of task.

When selecting a model, evaluate accuracy, cost, latency and scalability. Balancing these factors ensures the chosen solution aligns with your team’s capabilities, available resources, and long-term goals.

The AI universe is constantly evolving, and needs solutions that are not just designed for today, but for tomorrow. Proprietary systems often lock clients into specific technologies, making it costly and difficult to upgrade as AI capabilities advance. Look for open, future-proof AI systems that adapt to new technologies and workloads. This long-term flexibility gives you the confidence that their AI investments will remain viable, no matter how your needs evolve.

4. Use tools and accelerators to advance your AI & GenAI dev lifecycle

Don’t reinvent the wheel – use available cutting-edge tools and platforms to accelerate your GenAI projects. The goal is to streamline the process from data collection to actionable insights. Utilizing accelerators and pre-built tools can help you quickly move from concept to deployment, ensuring that your AI applications deliver value rapidly and efficiently.

If you are working on refining large language models (LLMs), platforms that offer distributed training and fine-tuning can significantly reduce the time from data to insights. These tools not only speed up development but also ensure that your AI models are optimized for performance and cost.

• To optimize AI pipelines, organizations can turn, for example, to the latest Intel Xeon processors with Intel Advanced Matrix Extensions (Intel AMX), a built-in AI accelerator. As part of Intel® AI Engines, Intel AMX was designed to balance inference, the most prominent use case for a CPU in AI applications, with more capabilities for training.
• To optimize Retrieval-Augmented Generation (RAG) pipelines, Langchain is a powerful tool for orchestrating workflows across different data sources. It connects language models with databases, APIs, and cloud storage, enabling seamless chaining of tasks like data retrieval and prompt transformation. This flexibility makes it easy to build scalable RAG systems that can quickly process and augment responses with relevant information.
• For managing embeddings, Amazon Bedrock Knowledgebase can offer a managed vector store solution that integrates with various embedding models. It provides scalable, efficient storage for embeddings, allowing fast retrieval of contextually relevant information from multiple data sources.
• By combining Langchain for orchestration and Bedrock for vector storage, you can build a highly efficient, adaptable RAG pipeline that accelerates insights and enhances AI applications.

By following these steps, you will be well on your way to implementing GenAI in a way that is both strategic and sustainable, driving meaningful outcomes for your organization.

The post Defining Your GenAI Data Strategy: A Roadmap for Enterprise Data Teams appeared first on Cloud Kinetics.

Why attend?

• Networking Opportunities: Engage with fellow CIOs and industry experts to share experiences and best practices.
• Expert Insights: Gain actionable advice on navigating cloud migration and modernization challenges.
• Strategic Planning: Align your IT strategy with the latest cloud technologies to drive innovation and business outcomes.

Agenda highlights

• Benefits of AWS Migration: Explore cost savings, security, scalability, and operational efficiency. Cloud
• Modernization Strategies: Discover how to accelerate digital transformation and optimize IT infrastructure.
• Productivity with Amazon Q: Learn how to automate and streamline migration and modernization processes.
• Customer Success Story: Hear from a leading organization that has successfully leveraged AWS for business growth.

Special offers

Eligible attendees will receive exclusive offers tailored to meet their business needs, ensuring that your participation translates into actionable insights.

The post CXO Roundtable <br> Unlock Business <br> Potential: Leveraging Modernization & Gen AI appeared first on Cloud Kinetics.

• Scaling AI with Cost-effective Infrastructure: Unlock the power of GenAI with a robust, resilient data foundation
  
• Real world Applications of Smart Cloud Solutions: Learn how leading enterprises unlock new revenue streams and drive innovation

Plus, eligible attendees can access exclusive offers and a complimentary pass to a special cocktail networking event in April.

The post Coffee Connect – Cloud & AI Innovation appeared first on Cloud Kinetics.

Join us for an engaging session on 27 March where we dive into how you can drive transformational business outcomes through strategic modernization-led migration, Data & GenAI.

Key Highlights:

• Making Data-Driven Decisions with Modernization: Enable faster, smarter decision-making and unlock greater business value through modernized systems
• Scaling AI with Cost-effective Infrastructure: Unlock the power of GenAI with a robust, resilient data foundation
• Proven Modernization Strategies: Go beyond lift-and-shift and modernize legacy applications to deliver superior customer experiences
• Real world Applications of Smart Cloud Solutions: Learn how leading enterprises significantly reduce time-to-market and unlock new revenue streams

Eligible attendees will receive a complimentary AI-powered ChatBot PoC Valued at S$15K or S$10K Service Credits*.

The post Coffee Connect: The Cloud & AI Advantage | SG Event appeared first on Cloud Kinetics.

Every client and customer cares deeply about security. Regardless of the domain, industry or specific application, when a workload is moved to or created in AWS, security and data protection are always important components of the architectural design. To meet these critical security requirements, organizations use AWS Control Tower and Landing Zones, which enable a secure and compliant foundation for your AWS environment.

Setting up an AWS Control Tower and Landing Zone

Setting up a Control Tower and Landing Zone for your enterprise applications can help mitigate many security risks and provide a consolidated and comprehensive view of your AWS landscape. AWS Control Tower and Landing Zone thoroughly propagate the concept of “define once and use across”. This enables you to set up a well-architected, multi-account environment in hours instead of weeks or months, utilizing best practice blueprints tailored to the organization’s needs.

As a security best practice, it is always recommended to have a multi-account approach, where accounts can be categorized based on application/environment/business-unit etc. This approach enhances security through segregation and isolation of workloads and data. This will also significantly reduce the surface attack area when there is a security compromise.

As your organization and customer needs grow, you will have a bunch of accounts to handle – that is when the Control Tower and Landing Zone comes to the rescue as it provides centralized control and policy management across the accounts.

Figure 1 here depicts how you can have all AWS accounts under AWS Organizations and tap on Control Tower features to enforce security and governance.

Setting up a Landing Zone is always one of the best approaches for customer applications running on multiple AWS accounts, if you want to ensure strict traffic inspection, central security logging, and cost savings.

Building a Landing Zone with AWS Control Tower: Core concepts

Here are the core concepts at play while establishing a robust AWS Control Tower and Landing Zone foundational implementation.

Organizational Units: When it comes to planning Organizational Units (OUs), there is no one-size-fits-all approach. It should be based on the best way you can categorize your workloads.

For example, an enterprise company with numerous applications, business units and multiple environments (e.g. Dev/UAT/Prod) can be structured as shown below.

Service Control Policies/Guardrails: Service Control Policies (SCPs) are effectively a policy-driven preventive guardrail. AWS SCPs/guardrails provide organizations with robust tools for optimizing and centrally managing governance, security & compliance enforcement, permission management and operational efficiency. These features make them critical components of a well-architected multi-account strategy in AWS. We recommend you enable all the required guardrails as per industry standards. To get started with AWS Best Practice guardrails, you can refer to the official AWS guidance documentation found here.

You could also create a Test OU within which you can enable and test the effect of guardrails without impacting any production workloads. This is prudent when teams may be unaware of how an SCP guardrail may impact your team’s day to day activities.

Networking for Landing Zone: This is the most important part which often consumes a lot of time for planning. We recommend that organizations should plan for three different types of traffic flow:

• Ingress traffic: The Landing Zone should have a highly available firewall for ingress traffic inspection. Organizations can choose from a number of firewall appliances in the market today, including native AWS Network Firewall.
• Egress traffic: Plan for a central NAT gateway to manage all the egress traffic originating from workload VPCs from all AWS accounts and ensure it is being inspected using the firewall. This saves cost when all your workload VPCs use a central NAT gateway instead of individual NAT gateways for VPCs and enhances security through comprehensive monitoring with a holistic view.
• Inter-VPC traffic: Also referred to as East-West traffic, this is internal traffic between the VPCs within the AWS accounts. Best practice is to have inter-VPC traffic inspected using a firewall to detect internal threats, prevent data exfiltration etc. However, you can choose to ignore inspection for some VPCs – for example, those which require high throughput and require less latency.

We recommend you further define any other flows for your workloads and analyse its effects including latency, costs when it traverses transit gateway, or other cost incurring components.

Figure 3 here shows one of the ways you can design your architecture to achieve the above-mentioned traffic inspection and flows. It uses hub and spoke architecture using AWS transit gateway.

To read more about hub and spoke architecture refer to this AWS article here.

Logging and monitoring: Logs can be considered as a critical asset in any infrastructure. There are a number of different kinds like VPC flow logs, firewall logs, DNS logs, transit gateway attachment logs, application logs, and more. AWS Control Tower offers you a way to centrally store these logs in a separate “Log Archive” account. While AWS Control Tower has the capability to implement centralized storage, the responsibility of log ingestion implementation is allocated to the organization. The logs can be further ingested to other Security Information and Event Management (SIEM) platforms for analytics.

Putting things in motion

By continuously monitoring workload performance and analysing customer feedback, organizations can effectively adjust resources and processes to align with evolving customer needs, ensuring enhanced service delivery and operational efficiency.

AWS offers native service called AWS CloudWatch, to get you started with Logging and Monitoring – refer to this official AWS documentation. This should help you understand what AWS services’ logs can be centralized, among other important notes.

To sum up, using the AWS Control Tower service will unveil a holistic view of security and governance across all AWS accounts within the organization. Setting up a Landing Zone makes it easier to have total control on all of the traffic entering and exiting your AWS accounts. This will significantly reduce the surface attack area and can efficiently create a scalable architecture and ensure security best practices.

For additional Design Consultation and Cloud Engineering support, Cloud Kinetics currently offers a refined AWS Secure Landing Zone (SLZ) implementation, available here via AWS Marketplace. You can also get in touch with us directly here.

The post AWS Control Tower and Landing Zone: Architecture & Best Practices appeared first on Cloud Kinetics.

According to a McKinsey evaluation, the key to GenAI success is in identifying practical applications that drive real business value rather than getting carried away by exaggerated claims.

Generative AI refers to AI systems that create new content, such as text, images, or music, based on their training data. Key to GenAI are Large Language Models (LLMs) and Foundation Models (FMs), designed to produce human-like text from extensive datasets. Central to GenAI are Large Language Models (LLMs) and Foundation Models (FMs),  which are designed to understand and produce human-like text. These models, trained on vast datasets, enable the generation of coherent and contextually relevant content.

Top 4 business benefits of GenAI applications for enterprises

Gartner forecasts that by 2026, over 80% of enterprises will integrate GenAI APIs or models into their operations, a dramatic increase from less than 5% in 2023.

Business benefits could include:

Enhance decision making

• Scenario planning
• Simulation & hypothesis testing
• Causal inference
• Decision support systems

Optimize business processes

• Document processing
• Data augmentation
• Process optimization
• Real-time decision making

Boost productivity & creativity

• Conversational search
• Summarization
• Content creation
• Code generation

Enhance customer experiences

• Chatbots
• Virtual assistants
• Conversation analytics
• Personalization

Enhance your decision making

Imagine a finance team at a global enterprise that regularly faces high-stakes decisions. Traditionally, analysts would sift through historical data, market trends, and economic indicators to forecast outcomes. Now, with GenAI, this process is not only faster but significantly more accurate.

For instance, the AI model analyses millions of data points from diverse sources in real-time, spotting correlations that even the most seasoned analyst might miss. The team can then leverage these insights to make split-second decisions on investments, risk management, and market strategies, ensuring they stay ahead of the competition.

Optimize business processes

Consider a manufacturing plant that operates 24/7. Equipment failures and unexpected downtime can lead to massive losses. With GenAI, the plant’s maintenance team doesn’t just react to problems — they prevent them.

GenAI systems continuously monitor machinery, analysing patterns and predicting failures before they happen. Picture a team receiving alerts on their tablets, detailing exactly which component is at risk and when it needs attention.

This proactive approach not only prevents costly disruptions but also optimizes resource allocation, as maintenance is performed only when truly necessary, reducing waste and boosting overall efficiency.

Boost productivity and creativity

In entertainment and media, staying relevant requires constant innovation. Picture a content creation team tasked with developing a new series. With GenAI, they’re not starting from scratch.

The AI suggests fresh storylines, generates character arcs, and even predicts audience preferences based on current trends. As the team collaborates with GenAI, they are able to push creative boundaries, producing content that resonates more deeply with audiences.

This blend of human creativity and AI-driven innovation results in ground breaking content that captivates viewers and sets new industry standards.

Enhance customer experience and engagement

Imagine an e-commerce team using GenAI to craft personalized recommendations for each customer based on their behaviour and purchase history. Instead of broad segments, customers receive tailored emails showcasing products they’re likely to love, boosting conversion rates and loyalty.

GenAI enables enterprises to deliver highly personalized and timely customer interactions, from tailored product recommendations in e-commerce to proactive support in retail, while also building emotional connections through personalized messaging. This enhances customer satisfaction, drives loyalty, and fosters long-term business growth.

GenAI use cases for 6 industries

GenAI is transforming various industries by enhancing functionality and efficiency.

Inventory & Sales Analytics

A textile retailer who once struggled with excessive inventory — leading to financial losses and wasted shelf space — can now leverage GenAI to analyse vast datasets like sales history, media trends, and customer preferences. This advanced analysis helps them accurately predict demand, enabling precise ordering for the upcoming season. As a result, they maintain optimal stock levels, reduce waste, free up shelf space, and improve profitability.

Risk Analytics

Retail chains often face challenges like fraudulent transactions and supply chain disruptions. By employing GenAI-driven risk analytics, they can detect anomalies in real time, allowing for intervention before issues escalate. For instance, a sudden spike in returns might be flagged as potential fraud, enabling immediate action and ensuring smooth operations.

Supplier Analytics

Managing multiple suppliers can be daunting, but with GenAI, retailers can assess and manage supplier performance more effectively. By analysing data on reliability, delivery times, and product quality, they can identify underperforming suppliers and make informed decisions, such as seeking alternatives or negotiating better terms, thereby strengthening their supply chain.

Customer Experience

Enhancement Retailers can significantly enhance the customer experience by offering personalized recommendations powered by GenAI. Analysing customer behaviour and preferences allows them to create tailored marketing campaigns and product suggestions, resulting in a more satisfying shopping experience that fosters long-term loyalty.

In the retail industry, information about inventory, sales, and suppliers is now readily available at the click of a button. Businesses can understand risks and make more informed decisions, which was unimaginable just six months ago.

Smart Claims Management

Insurance companies often struggle with slow claims processing, but GenAI offers a solution by automating this process, making it faster and more accurate. When a customer files a claim, the AI can instantly review documentation, verify information, and process the payment, reducing the waiting time from weeks to just days.

Data Enrichment

To improve risk assessment models, insurers can use GenAI to enrich their data by integrating information from various sources, including social media, weather forecasts, and historical claims data. This comprehensive view allows for more accurate risk assessments, leading to better pricing and more effective customer service.

KYC

With GenAI, customer service teams can access a complete view of each policyholder’s profile. The AI compiles data from various touchpoints, ensuring compliance with KYC regulations and enabling more personalized service, such as offering relevant policy updates or efficiently responding to inquiries.

Even in traditional industries like insurance, GenAI is levelling up smart claims management. Companies are beginning to use intelligent document processing to ensure high-quality, consistent service.

Route Optimization

Logistics companies can significantly reduce delivery times and fuel costs with GenAI-driven route planning. By analysing traffic patterns, weather conditions, and delivery schedules, GenAI creates the most efficient routes, leading to faster deliveries and happier customers.

Demand Forecasting

Airlines anticipating surges in bookings, particularly around holidays, can benefit from GenAI’s predictive analytics. This technology forecasts demand, allowing airlines to allocate resources effectively, whether by adding more flights or adjusting prices to maximize revenue.

Supply Chain Optimization

Global shipping companies looking to enhance efficiency can rely on GenAI to optimize supply chain operations. By analysing data on shipping routes, fuel consumption, and port congestion, GenAI helps reduce delays, lower costs, and improve overall service quality.

Government agencies are beginning to use GenAI to make their services much more user-friendly. Citizens can now retrieve information more easily, improving their experience with public services.

Citizen Services

Self-help government services can be made more accessible and user-friendly with AI-powered chatbots. These virtual assistants provide quick and accurate information, such as answering tax filing questions or guiding users through permit applications, enhancing the overall citizen experience.

Intelligent Document Processing and Validation

Government agencies overwhelmed with paperwork can turn to GenAI for automating document processing and validation. Whether it’s passport applications or business licenses, GenAI ensures faster turnaround times and reduces the likelihood of errors.

Risk Analytics

Banks can leverage GenAI to assess and manage financial risks by analysing market trends, credit scores, and transactional data. This allows them to identify potential threats and take preventative measures, minimizing losses and safeguarding their operations.

Collection Analytics

Improving debt collection processes becomes more efficient with GenAI. By analysing customer payment histories and behaviour patterns, the AI can prioritize collections, increasing recovery rates and streamlining operations.

Portfolio Analytics

Investment teams can optimize portfolio performance using GenAI, which provides insights into market movements and potential risks. These insights help the team make informed decisions, maximizing returns for their clients.

Customer Analytics

Banks aiming to offer personalized banking experiences can utilize GenAI to analyse customer data, providing tailored financial advice and recommending relevant products. This personalized approach enhances customer satisfaction and loyalty.

Manufacturing companies are beginning to use GenAI to make high-quality decisions in inventory planning and supply chain management. This technology provides real-time insights that were unimaginable just a short time ago.

Inventory Monitoring

Manufacturers can track and manage inventory in real-time with GenAI. The AI monitors stock levels, predicts demand, and alerts the team to reorder materials before they run out, preventing production delays and reducing costs.

Supplier Analytics

Manufacturing companies can assess supplier performance using GenAI by analysing delivery times, product quality, and pricing. This allows them to choose the best suppliers, negotiate better terms, and maintain a reliable supply chain.

Process Automation

Factories can optimize production processes with GenAI, reducing downtime and increasing efficiency. This automation leads to lower costs and higher output, making operations more streamlined.

Production Planning

Production teams can create efficient schedules using GenAI by analysing data on resource availability, machine capacity, and market demand. This ensures orders are fulfilled on time and within budget.

The post GenAI for Enterprises: Top Benefits, Impact And Industry Use Cases appeared first on Cloud Kinetics.

The highlights section includes a financial profile summing up all the important financial numbers of the report and relevant business information. The customer wanted to utilize GenAI technology to optimize its business report-building process by summarizing the financial profile of every company.

The post GenAI-Powered Data Solution Delivers Tangible Results For A Financial Service Provider appeared first on Cloud Kinetics.

Our CXO Roundtable conducted on 30 Jan in Bengaluru offered a unique opportunity to discover innovative IT & business strategies for optimizing cloud infrastructure and business performance. Attendees learned how to right-size resources, leverage spot and reserved instances, and automate scaling processes to enhance cloud efficiency.

What was covered:

• Fuelling Growth with Scalable Cloud Technology: How scalable cloud platforms can enhance operational efficiency and agility, helping businesses stay competitive.
• Mastering FinOps for Cost Optimization: Strategies that can reduce cloud spending by up to 30% while maintaining optimal performance, maximizing ROI.
• Enhancing Data Security and Compliance: Robust cloud solutions to safeguard data and meet compliance requirements, a critical consideration for organizations.
• Driving Customer-Centric Innovation: How modernizing legacy systems can improve customer experiences and foster loyalty through tailored solutions.
• Harnessing AI for Business Transformation: The role of AI streamlined operations and informed decision-making in unlocking innovation and growth opportunities.

The post CXO Roundtable Dinner & Cloud Transformation Summit appeared first on Cloud Kinetics.

The post A Strong Data Foundation, Analytics & AI Fuel Growth For A Health Tech appeared first on Cloud Kinetics.

In this webinar, we explored how Content Delivery Networks (CDNs) serve as a powerful tool to supercharge performance, optimize content delivery, and shield digital assets from threats.

The session provided insights into:

• CDN Fundamentals: Understanding the core concepts of CDNs and their impact on performance and user experience.
• Real-World Applications: Practical use cases of CDNs in addressing specific challenges.
• Security First: Key threats mitigated by CDNs and strategies to protect digital assets.
• Performance Optimization: Techniques to enhance content delivery and reduce load times.
• Edge Computing and the Future: The synergy between edge computing and CDNs, and the future of content delivery.
• CDN Selection and Best Practices: Guidance on choosing the right CDN provider and implementing effective strategies.

Other Highlights:

• Exclusive AWS & Cloud Kinetics Offers: Eligible attendees unlocked special discounts tailored to their business needs.
• Interactive Q&A Session: Participants asked pressing questions and received real-time answers from experts.

Panelists:

Anand Vimal

Sr. Director, Digital Cloud Transformation - Cloud Kinetics

Annappa Patil

Sr BDM Edge & Elemental
AWS

Praveen Hosur Narayana Gupta

Senior Solutions Architect
AWS

Mayank Pandey

Senior Solutions Architect
Cloud Kinetics

The post Elevate Your Digital Presence: <br> A Deep Dive into CDN <br> Performance and Security appeared first on Cloud Kinetics.